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Volumn 2006, Issue , 2006, Pages 497-500

Automatic option generation in hierarchical reinforcement learning via immune clustering

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; IMMUNOLOGY; INTELLIGENT AGENTS; ONLINE SYSTEMS; PROBLEM SOLVING;

EID: 33750954561     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (12)
  • 2
    • 0033170372 scopus 로고    scopus 로고
    • Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning
    • Jan.
    • R.S. Sutton, D. Precup, S.P. Singh, "Between MDPs and semi-MDPs: A framework for temporal abstraction in reinforcement learning," Artificial Intelligence, vol.112, pp.181-211, Jan. 1999.
    • (1999) Artificial Intelligence , vol.112 , pp. 181-211
    • Sutton, R.S.1    Precup, D.2    Singh, S.P.3
  • 4
    • 0002278788 scopus 로고    scopus 로고
    • Hierarchical reinforcement learning with the MAXQ value function decomposition
    • T.G. Dietterich, "Hierarchical reinforcement learning with the MAXQ value function decomposition," Journal of Artificial Intelligence Research, vol.13, pp.227-303, 2000.
    • (2000) Journal of Artificial Intelligence Research , vol.13 , pp. 227-303
    • Dietterich, T.G.1
  • 5
    • 0004782095 scopus 로고    scopus 로고
    • Learning hierarchical control structures for multiple tasks and changing environments
    • Zurich, Switzerland
    • B.L. Digney, "Learning hierarchical control structures for multiple tasks and changing environments," in Proc. of the 15th International Conference on Simulation of Adaptive Behavior, Zurich, Switzerland, 1998. pp.321-330.
    • (1998) Proc. of the 15th International Conference on Simulation of Adaptive Behavior , pp. 321-330
    • Digney, B.L.1
  • 6
    • 0013465187 scopus 로고    scopus 로고
    • Autonomous discovery of subgoals in reinforcement learning using deverse density
    • San Fransisco: Morgan Kaufmann
    • A. McGovern, A. Barto, "Autonomous discovery of subgoals in reinforcement learning using deverse density," in Proc. of the 8th International Conference on Machine Learning, San Fransisco: Morgan Kaufmann, 2001. pp.361-368.
    • (2001) Proc. of the 8th International Conference on Machine Learning , pp. 361-368
    • McGovern, A.1    Barto, A.2
  • 7
    • 84945250000 scopus 로고    scopus 로고
    • Q-cut: Dynamic discovery ofsub-goals in reinforcement learning
    • Springer
    • I. Menache, S. Mannor, N. Shimkin, "Q-cut: dynamic discovery ofsub-goals in reinforcement learning," in Volume 2430 of Lecture Notes in Computer Science, Springer, 2002. pp.295-306.
    • (2002) Lecture Notes in Computer Science , vol.2430 , pp. 295-306
    • Menache, I.1    Mannor, S.2    Shimkin, N.3
  • 9
    • 0015956495 scopus 로고
    • Towards a network theory of the immune system
    • Jan.
    • N. K. Jerne, "Towards a network theory of the immune system," Annual Immunology, vol. 125C, pp.373-389, Jan. 1974.
    • (1974) Annual Immunology , vol.125 C , pp. 373-389
    • Jerne, N.K.1
  • 12
    • 0000123778 scopus 로고
    • Self-improving reactive agents based on reinforcement learning, planning and teaching
    • Apr.
    • L. G. Lin, "Self-improving reactive agents based on reinforcement learning, planning and teaching," Machine Learning, vol. 8, pp.293-321, Apr. 1992.
    • (1992) Machine Learning , vol.8 , pp. 293-321
    • Lin, L.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.